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Beyond conventional sentiment indicators: Cryptocurrency's hidden potential in VIX forecasting

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  • Gu, Ming
  • Lin, Juan
  • Liu, Siyi

Abstract

This study identifies cryptocurrency overnight returns, defined as price changes during U.S. equity market closures, as effective predictors of the VIX. These returns capture retail investor sentiment during non-trading hours, evidenced by overnight-to-trading-hour return reversals that intensify with investor attention. These sentiment signals, when incorporated into standard forecasting models, significantly improve out-of-sample VIX forecasting accuracy and generate superior economic performance through VIX-based trading strategies. These findings reveal a novel transmission channel where sentiment formed in 24/7 cryptocurrency markets predicts next-day equity market volatility, highlighting the increasing integration between digital assets and traditional finance.

Suggested Citation

  • Gu, Ming & Lin, Juan & Liu, Siyi, 2026. "Beyond conventional sentiment indicators: Cryptocurrency's hidden potential in VIX forecasting," Economic Modelling, Elsevier, vol. 161(C).
    • Handle: RePEc:eee:ecmode:v:161:y:2026:i:c:s026499932600177x
    DOI: 10.1016/j.econmod.2026.107648
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